Text categorization with Lee model

Xiaobo Jin; Qingguo Xia

Text categorization with Lee model

Xiaobo Jin^*, Qingguo Xia

^*Corresponding author for this work

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

Abstract

David Lee came up a model with a psychologically method considering text categorization. This paper introduces Lee's model in Naive Bayes and TFIDF, compares two different vector representation-influence and TFIDF which sway the classification precision and analyzes two factors which effect the algorithm differently in the model. In the end, experiments show that heuristic method and influence representation can improve Naive Bayes greatly at much lower time cost.

Original language	English
Pages (from-to)	175-176+222
Journal	Jisuanji Gongcheng/Computer Engineering
Volume	32
Issue number	2
Publication status	Published - 20 Jan 2006
Externally published	Yes

Keywords

Lee's model
Naive Bayes
TFIDF
Text categorization

Cite this

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Text categorization with Lee model

Abstract

Keywords

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